Major Depressive Disorder (MDD) is one of the leading causes of disease burden worldwide and is characterized by a high relapse rates. In spite of decades of research, findings have not translated into a reliable model of MDD that can be used to test novel therapeutic interventions. This modest progress might partially stem from the heterogeneous nature of MDD and the fact that animal models cannot probe key symptoms of MDD, including depressed mood, guilt or rumination. Within the context of reinforcement learning (RL) theories, anhedonia, depressed mood, inability to make decisions and excessive guilt may be explained by deficits in learning about rewards and punishments and a failure to update behavior accordingly. Consistent with this theory, MDD individuals show reduced reward and increased punishment learning. Of note, reduced reward responsiveness might persist after remission, whereas punishment processing normalizes when symptoms abate, suggesting that abnormal reward, but not punishment, learning might represent a trait marker of MDD. In spite of these promising leads, the neurobiological mechanisms underlying these dysfunctions remain unknown. Critically, animal studies have shown that dopamine (DA) transmission in the ventral tegmental area (VTA) and gamma-aminobutyric acid (GABA) signals originating from the lateral habenula (LHb), as well as interactions between these systems, influences RL. These interactions modulate DA release and basal ganglia (BG) activity, which helps organisms to choose or avoid an action. Despite compelling evidence from animal studies for these interactions, these processes have not been tested in MDD. The goal of the proposed research is to fill this critical gap and take us one-step closer to developing a mechanistic model of RL dysfunction in MDD. To achieve this goal, we will integrate an innovative multi-modal molecular and functional neuroimaging approach to test RL in 60 subjects (20 HC, 20 MDD and 20 rMDD). To this end, baseline GABA levels in the BG will be measured using a novel multi-voxel MRS technique, followed by an fMRI session while participants complete a social RL task. This will allow us to investigate the neural correlates of learning deficits in MDD and the influence of GABA on RL. We hypothesize that controls will exhibit reward learning signals in the BG and punishment signals in the LHb. Consistent with our proposal that MDD is an RL disorder, we hypothesize that MDD will show blunted reward and punishment signals in the BG and LHb, respectively. This abnormal pattern in MDD will be linked to enhanced punishment and reward signals in the BG and LHb, respectively. In addition, parsing state/trait effects of MDD, we hypothesize that reward and not punishment learning deficit will be observed in rMDD. Lastly, we hypothesize that baseline GABA levels will predict RL in all groups.